Summary of Website Journeys

Below is a summary of what we found when checking the rsid report suite looking at data from start_date to end_date

Note: The raw data for everything that follows is available in [this Google Sheet].

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Results

All Journeys

All major journeys across the National Trust website areas.

Landing Pages

First pages of a user journey.

Device

Journeys from specfic devices or operating systems.

Commercial

Any journey that contains a commercial journey.

Top Level

Journeys from the home page onward to other significant areas of the website.

Property Pages

Journeys to a NT property page.

Discovery

Journeys categorised as a research or discovery journey.

Journeys in Detail

Number of Journeys Higher or Lower than the Baseline
Higher Lower
31 12
31 12

Heatmaps

Insights:

Anomaly Analysis By Journey

Below is the count of anomalies detected for each journey, this is sorted by the number detected in the post launch period. Journeys higher up this list will need more investigation than lower journeys.

Positive anomalies are where the visit data exceeded the upper boundary of the data window. Negative anomalies are where the visit data fell below the lower boundary of the data window. The Net value is an overall count of the anomalies: (Positive Anomalies - Negative Anomalies = Net).

Higher negative values for Net columns indicate the journey fell below the expected amounts for the journey. 1 Anomaly = 1 day where the data was above or below expectations.

Pre Launch Anomalies
Post Launch Anomalies
Journey Name Positive Negative Net Positive Negative Net
Home to Our Cause 3 15 -12 0 46 -46
Home to Holidays 4 22 -18 1 26 -25
Commercial: Holidays Checkout Steps 1-4 3 25 -22 1 25 -24
Home to Support 4 18 -14 0 19 -19
Home to Art 1 18 -17 1 15 -14
Home to Days Out 5 8 -3 1 13 -12
Home to Donate Form 3 15 -12 1 13 -12
Home to Search Results 7 10 -3 0 12 -12
Home to Shop 6 11 -5 0 12 -12
Home to Join 7 15 -8 2 12 -10
Days Out Entry 5 15 -10 4 13 -9
Commercial: Membership Checkout Steps 1-4 4 15 -11 4 11 -7
Days Out to Places Map 5 12 -7 4 10 -6
Days Out to Property Page 6 15 -9 2 8 -6
Holidays Entry 6 11 -5 1 7 -6
Homepage Entry 9 5 4 1 7 -6
Shop Entry 8 4 4 1 6 -5
Days Out to Places Search 5 7 -2 4 8 -4
ALL Mobile 7 6 1 2 5 -3
Join Us Entry 6 17 -11 4 7 -3
ALL Main Site 9 4 5 4 6 -2
ALL Android 8 6 2 5 6 -1
ALL Apple iOS 7 5 2 5 6 -1
Commercial: Donate Checkout Steps 1-2 3 10 -7 3 4 -1
Property Page Seen 8 5 3 6 7 -1
ALL Direct Traffic 10 4 6 5 5 0
ALL New Visitors 6 7 -1 5 5 0
ALL PPC 3 2 1 6 6 0
ALL Repeat Visitors 7 6 1 5 5 0
ALL Visits 7 7 0 5 5 0
Commercial: Shop Checkout Steps 1-4 2 8 -6 0 0 0
ALL Natural Search 5 6 -1 5 4 1
ALL SEO 5 6 -1 5 4 1
ALL Tablet 12 11 1 4 3 1
ALL Desktop 7 9 -2 3 1 2
ALL Paid Social 6 2 4 4 2 2
ALL Shop 1 5 -4 2 0 2
Commercial: Renew Checkout Steps 1-3 7 7 0 7 5 2
Members Area Entry 13 2 11 4 1 3
ALL Holidays 4 1 3 9 3 6
ALL Social 9 4 5 7 1 6
ALL Affiliates 2 4 -2 10 3 7
ALL Email 11 3 8 13 0 13

Baseline Summary

Below is a summary of the website journeys looking at data from 2021-11-17 to 2022-05-05. This table is sorted by the difference between the baseline and the new site baseline difference percentage. Poor performing new journeys should come to the top.

Journey Name Baseline Visits New Site Visits Avg. % Visits Diff.
Shop Entry 5249 1575 -70.0
Commercial: Shop Checkout Steps 1-4 585 200 -65.8
Commercial: Donate Checkout Steps 1-2 436 175 -59.9
ALL Shop 7665 3360 -56.2
Home to Shop 1696 896 -47.2
ALL Email 8481 4911 -42.1
Commercial: Holidays Checkout Steps 1-4 284 194 -31.7
Holidays Entry 2979 2268 -23.9
ALL Paid Social 2488 1899 -23.7
Members Area Entry 1227 1082 -11.8

Anomaly Plots By Journey

Baseline Dates: 2021-11-17 to 2022-02-14. Launch Dated (Red Line): 2022-02-15 to 2022-05-15.

Commercial Analysis

Membership

Insights:

Summary

Funnels

Journeys

Metrics

mpg_list <- split(mtcars$mpg, mtcars$cyl)
disp_list <- split(mtcars$disp, mtcars$cyl)
inline_plot <- data.frame(cyl = c(4, 6, 8), mpg_box = "", mpg_hist = "",
                          mpg_line1 = "", mpg_line2 = "",
                          mpg_points1 = "", mpg_points2 = "", mpg_poly = "")
inline_plot %>%
  kbl(booktabs = TRUE) %>%
  kable_paper(full_width = FALSE) %>%
  column_spec(2, image = spec_boxplot(mpg_list)) %>%
  column_spec(3, image = spec_hist(mpg_list)) %>%
  column_spec(4, image = spec_plot(mpg_list, same_lim = TRUE)) %>%
  column_spec(5, image = spec_plot(mpg_list, same_lim = FALSE)) %>%
  column_spec(6, image = spec_plot(mpg_list, type = "p")) %>%
  column_spec(7, image = spec_plot(mpg_list, disp_list, type = "p")) %>%
  column_spec(8, image = spec_plot(mpg_list, polymin = 5))
cyl mpg_box mpg_hist mpg_line1 mpg_line2 mpg_points1 mpg_points2 mpg_poly
4
6
8
# https://cranky-chandrasekhar-cfefcd.netlify.app/
# https://haozhu233.github.io/kableExtra/awesome_table_in_html.html#Row_spec

Flows

Membership conversions by Channel. Start: 2022-05-08 to 2022-05-15.

Forecast

Renewals

Insights:

Summary

Funnels

Journeys

Metrics

Flows

Renewals conversions by Channel. Start: 2022-05-08 to 2022-05-15.

Forecast

Holidays

Insights:

Summary

Funnels

Journeys

Metrics

Flows

Forecast

Shop

Insights:

[Min] The lowest amount of Shop - Order Step 4 - Order Confirmation (Serialized) (ev182) was 15, which occurred on Feb. 3rd and was 84% less than the average of 92.

Summary

head(mtcars)
##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

Funnels

We show the data in this tab.

Start: 2022-05-01 to 2022-05-07.

Last 7 days funnel performance Hover over for fallout details at each stage.

Start: 2022-05-08 to 2022-05-14.

Sales & Revenue

Here is the individual trends for each metric in the shop funnel.

Revenue:

Shop Orders:

Shop - Order Step 4 - Order Confirmation (Serialized) (ev182)

Metrics

Here is the individual trends for shop sales. Add Revenue events too.

Date Range Journey Name Step 1 Step 2 Step 3 Step 4 - Confirmation
2022-05-01 to 2022-05-07 Commercial: Shop Checkout Steps 1-4 449 342 342 316

Flows

Shop conversions by Channel. Start: 2022-05-08 to 2022-05-15.

Forecast